In retail sale stores, a great deal of time and effort is directed to the task of physical layout. Many product placement decisions are made based upon estimates of consumer behavior in an effort to place products in a location that maximizes the likelihood that they will be observed and purchased by a customer. Consider the example of a retail pharmacy, for example. In many pharmacies, prescription medicines are dispensed in the rear of the pharmacies' physical plant. This physical layout is not accidental; the layout is premised on an assumption that customers enter pharmacies in order to purchase prescription medicines. By dispensing prescription medicines in the rear of the pharmacies' physical plant, the pharmacy requires customers to pass through the interior of the store where they may observe other products offered by the store. In theory, it raises the probability that the customers will make impulse purchases of other items. This arrangement is predicated on an assumption that customers enter pharmacies to buy prescription medicines.
It is a difficult and expensive task to determine how consumers decide to buy particular goods or services (“products”). Retailers spend great sums of money commissioning studies and other investigations to determine why a customer entered a particular store or why the customer determined to purchase particular products. Some consider surveys of customers to be unreliable. The mere fact that a customer is questioned about his buying habits tends to skew the survey results because, by questioning the customer directly, the customer ceases to think intuitively. Instead, the customer may over-think a purchasing decision. Additionally, only a small sample of the buying public may be surveyed with reasonable cost. There can be no guarantee that the survey will accurately reflect the buying decisions of the public at large particularly when buying decisions reflect impulsive behavior.
Other methods for measuring and evaluation customer behavior are known. Typically, they require some type of customer surveillance to monitor purchasing decisions as they are made. However, such surveillance is expensive, time-consuming and cannot be done on a large scale. Thus, the same problem of undersampling arises when customer surveillance is performed.
There is a need in the art for a system that can identify customer motivations from customer purchasing decisions. Further, there is a need in the art for a system that can identify customer motivations using a large statistical base at low cost.